britt session vii tuesday (variability) small file

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The Snap Sampler tm Sampling Variability Sampling Variability and Trend Monitoring and Trend Monitoring North American Environmental Field Conference Tampa, Florida January 15, 2007 Mr. Sandy Britt, PG, CHG ProHydro, Inc. Fairport, New York [email protected] Fewer Variables with SNAP SAMPLER 30 35 40 45 50 55 60 65 70 0 4 8 12 16 20 24 Sampling events Concentration 30 35 40 45 50 55 60 65 70 0 4 8 12 16 20 24 Sampling events Concentration Low noise data High noise data

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Page 1: Britt Session Vii Tuesday (Variability) Small File

The Snap Sampler tm

Sampling VariabilitySampling Variabilityand Trend Monitoringand Trend Monitoring

North American Environmental Field

ConferenceTampa, Florida

January 15, 2007

Mr. Sandy Britt, PG, CHGProHydro, Inc.

Fairport, New [email protected]

Fewer Variables with SNAP SAMPLER

30

35

40

45

50

55

60

65

70

0 4 8 12 16 20 24

Sampling events

Con

cent

ratio

n

Many Variables with Purge and Pour

30

35

40

45

50

55

60

65

70

0 4 8 12 16 20 24

Sampling events

Con

cent

ratio

n

Low noise data

High noise data

Page 2: Britt Session Vii Tuesday (Variability) Small File

What are sources of data error and variability?

Laboratory?Hold timeCross-contaminationManual vs. autosampler

Collection Method?Bail purge and samplePump purge and sampleLow flow purge and samplePassive (noPassive (no--purge) samplingpurge) sampling

Sample Handling?Bottle fillingTransport

Page 3: Britt Session Vii Tuesday (Variability) Small File

Dye source with gravity feed to injection port

Simulated 4-inch well

Upgradient/ influent reservoir

Piezometers

Dye port

Constant head reservoir

Homer’s water supply bucket

Influent supply from constant head reservoir Effluent drain

Effluent reservoir

DTSC Sand Tank Well Model“homogeneous” model well

Page 4: Britt Session Vii Tuesday (Variability) Small File

Britt, SL, 2005, Testing the In-Well Horizontal Laminar Flow Assumption with a Sand Tank Well Model. Ground Water Monitoring and Remediation 25, no. 3 p.73-81

percent of initial dye concentration

33%

40%

35%

Flow weighted averaging

Flow-weighted averaging effect

Page 5: Britt Session Vii Tuesday (Variability) Small File

∇ Water chemistry changes as a well is pumped

∇ Why does chemistry change?

∇ “Stagnant” water?

Or…

∇ A varying mix of water entering the pump?

Active (Purge) Sampling Methods

Page 6: Britt Session Vii Tuesday (Variability) Small File

Varljen, et al., 2006, Numerical Simulations to Assess the Monitoring Zone Achieved during Low-Flow Purging and Sampling, GWMR, 26: p. 44-52

Analysis of

Steady-State

purging

Hydraulics controls flow, including water coming from beyond the screen zone

But purge time controls what water discharges from the pump

Traditional and Low Flow Purging Static vs. Dynamic

Page 7: Britt Session Vii Tuesday (Variability) Small File

Stability parameters monitored…

Achieving “stability” depends on:

∇ Pre-purge well stratification∇ Stratification in the aquifer∇ Inflow characteristics∇ Shadow effects in the aquifer∇ Density effects

∇ Stability criteria∇ Barn door (e.g. 10%)∇ Reasonable measures (EC or

ORP +/- 10 units, without directional drift)

∇ How often you measure

Purge Equilibration

This is what “Stability”looks like

Page 8: Britt Session Vii Tuesday (Variability) Small File

How long does purge equilibration take?

Achieving true “stability” (i.e. flow-weighted-average)depends on:

∇ Well diameter∇ Well length∇ Pump position∇ Contaminant position∇ Other heterogeneity

Quick Calculation:4” well, 10 foot screen, pump in the middle,

250 ml/min purge rate

(2.5L/ft)*5 ft/(0.25L/min) = 50 min (plug flow)

>50 minutes

Not too long????

Page 9: Britt Session Vii Tuesday (Variability) Small File

What about Sampling Passively?

What is Passive Sampling?

Sampling without purgingSampling without purging>Deploy in advance>Deploy in advance>Relies on >Relies on ““passivepassive”” flushingflushing

Examples:Polyethylene Diffusion Bag sampler (USGS)Rigid Porous Pipe sampler (USGS)Dialysis Membrane Sampler (USGS)Gore Sorber (WL Gore)

Snap Sampler (ProHydro)

Page 10: Britt Session Vii Tuesday (Variability) Small File

• Natural flow delivered to well

• Ambient (passive) mixing according to native flow dynamics

• Stratification testing?

• Sample from same position(the key to consistency)

Passive EquilibrationCan Limit Variables

Page 11: Britt Session Vii Tuesday (Variability) Small File

The Snap Sampler is a dedicatedpassive sampling system

• Deploy double-ended bottles in an open position.

• Sample after short or long residence time in the well—1-2 weeks or 3 or 6 months

• Mechanical or electric trigger closes bottles in situ.

• Sample transfer is not requiredSample transfer is not requiredat the well head for VOCs-No exposure to air

Page 12: Britt Session Vii Tuesday (Variability) Small File

How the Snap Sampler works….

Insert

40ml 125ml

Set Snap Cap

• Load & Set Snap Caps

Page 13: Britt Session Vii Tuesday (Variability) Small File

How the Snap Sampler works…continued

Lower downhole

• Modular samplers allow up to 4 bottles per trigger

• Multiple triggers can be used for multiple sampling depths

Hang on Dock Ring Secure

• Mechanical or electric trigger

Attach Trigger

Page 14: Britt Session Vii Tuesday (Variability) Small File

Seal in situ,

reduce surface handling

In Situ:

• Sample at the same position each sampling event

• Sample collection takes place submerged in the well

No well-head sample transfer required

Page 15: Britt Session Vii Tuesday (Variability) Small File

• Very good correlations

• VOCS, 1,4-dioxane, anionsParsons, 2005, McClellan Air Force Base, Sacramento, CA

Example data

Page 16: Britt Session Vii Tuesday (Variability) Small File

Spotting data trends may depend on consistency of your collection method…

Many variables for purge:Many variables for purge:actual concentration, pump position, pumping duration, stability criteria requirements, wind, temperature, site surface or ambient air contamination, bottle fill rate, pour technique, speed of bottle closure, filtration, transport, analytical variability.

Fewer variables Fewer variables with with in situ sealedin situ sealedsamples:samples: actual concentration, transport, analytical variability.

Page 17: Britt Session Vii Tuesday (Variability) Small File

Interpretation of simple data trendssimple data trends is easier with less random error

Illustration only, not site data

Simple Declining Trend

20

25

30

35

40

45

50

55

60

65

70

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Sampling event

Con

cent

ratio

n

"Actual"

30% Random

2025303540455055606570

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Sampling event

Con

cent

ratio

n

10% Random

2025303540455055606570

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Sampling event

Con

cent

ratio

n

Page 18: Britt Session Vii Tuesday (Variability) Small File

Interpretation of more complicatedmore complicated data trends is easier with less random error

Illustration only, not site data

Declining then Increasing Trend

2025303540455055606570

1 3 5 7 9 11 13 15 17 19 21 23

Sampling event

Con

cent

ratio

n"Actual"

10% Random

2025303540455055606570

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Sampling event

Con

cent

ratio

n

30% Random

2025303540455055606570

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Sampling event

Con

cent

ratio

n

Page 19: Britt Session Vii Tuesday (Variability) Small File

Interpretation of very complicatedvery complicated data trends is easier with less random error

Illustration only, not site data

Complex Trend

2025303540455055606570

1 3 5 7 9 11 13 15 17 19 21 23

Sampling event

Con

cent

ratio

nActual

10% Random

2025303540455055606570

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Sampling event

Con

cent

ratio

n

30% Random

2025303540455055606570

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Sampling event

Con

cent

ratio

n

Page 20: Britt Session Vii Tuesday (Variability) Small File

Example Data Variation

0

20

40

60

80

100

120

140

160

Sampling Quarter

TCE

mic

rogr

ams

per l

iter

purge 24.3 134 54.9 120 28.9 92.7 71 5.6 12.6

1 2 3 4 5 6 7 8 9

Example Data Variation

0

20

40

60

80

100

120

140

160

Sampling Quarter

TCE

mic

rogr

ams

per l

iter

Snap 56.9 72.6 64.1 103.0 39.7 65.6 40.9 50.8 50.4

1 2 3 4 5 6 7 8 9

TCE Example, site in Southern California

Range: 5.6 to 134Avg. RPD Q to Q: 100%Median RPD Q to Q: 94%

Private site, unpublished data

Range: 39.7 to 103Avg. RPD Q to Q: 36%Median RPD Q to Q: 35%

Purge Sealed in situ

Pump purge and bail sample Passive Snap Sample

Page 21: Britt Session Vii Tuesday (Variability) Small File

TCE Example, Quarter to Quarter change

Example Data Variation

0

20

40

60

80

100

120

140

160

Sampling Quarter

TCE

mic

rogr

ams

per l

iter

Snap 56.9 72.6 64.1 103.0 39.7 65.6 40.9 50.8 50.4

purge 24.3 134 54.9 120 28.9 92.7 71 5.6 12.6

1 2 3 4 5 6 7 8 9

Relative Percent DifferenceQuarter to following quarter

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

1 2 3 4 5 6 7 8

Event

RPD

Snap Sample Pump Purge

TCE data superimposed Quarter to Quarter Relative Change

• Directional dynamic unchanged

• Quarterly concentration change less exaggerated

Page 22: Britt Session Vii Tuesday (Variability) Small File

Overall statistics indicate differences in methods:

Purgen = 100 comparison pairs

Mean RPD Q to Q: 66%

Median RPD Q to Q: 51%

Mean % change Q-Q: 298%Median % change: Q-Q: 71%

Sealed in situn = 81 comparison pairs

Mean RPD Q to Q: 48%

Median RPD Q to Q: 37%

Mean % change Q-Q: 138%Median % change: Q-Q: 55%

Note: differences include the actual changes in

concentration…

Page 23: Britt Session Vii Tuesday (Variability) Small File

• Reduced variation possible through consistent downhole passive sampling method

• In Situ sealed samples avoid error from surface handling

www.SnapSampler.com

Harbec Plastics Ontario, New York

“Technical Innovation with Environmental Responsibility”

• Passive method adds consistency by avoiding variables introduced during purge step

• Data trend more closely reflects downhole condition